Image Segmentation
Flair
Keras
tensorflow
medical-imaging
white-matter-hyperintensities
mri
deep-learning
neurology
multiple-sclerosis
Instructions to use Bawil/wmh_leverage_normal_abnormal_segmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Flair
How to use Bawil/wmh_leverage_normal_abnormal_segmentation with Flair:
from flair.models import SequenceTagger tagger = SequenceTagger.load("Bawil/wmh_leverage_normal_abnormal_segmentation") - Keras
How to use Bawil/wmh_leverage_normal_abnormal_segmentation with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Bawil/wmh_leverage_normal_abnormal_segmentation") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -234,7 +234,7 @@ Mahdi Bashiri Bawil, Mousa Shamsi, Ali Fahmi Jafargholkhanloo, Abolhassan Shaker
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title={Incorporating Normal Periventricular Changes for Enhanced Pathological
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White Matter Hyperintensity Segmentation: On Multi-Class Deep Learning Approaches},
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author={Bawil, Mahdi Bashiri and Shamsi, Mousa and Jafargholkhanloo, Ali Fahmi and
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Bavil, Abolhassan Shakeri
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year={2025},
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note={Models: https://huggingface.co/Bawil/wmh_leverage_normal_abnormal_segmentation}
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}
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title={Incorporating Normal Periventricular Changes for Enhanced Pathological
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White Matter Hyperintensity Segmentation: On Multi-Class Deep Learning Approaches},
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| 236 |
author={Bawil, Mahdi Bashiri and Shamsi, Mousa and Jafargholkhanloo, Ali Fahmi and
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Bavil, Abolhassan Shakeri},
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year={2025},
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note={Models: https://huggingface.co/Bawil/wmh_leverage_normal_abnormal_segmentation}
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}
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